Experiments are often conducted on computer models or designed by computer models. In some experiments, it is useful to distribute design points uniformly across a design space to observe responses in the experiment for different input factors at that design point. Such a design can be considered a space-filling design. For instance, if an experiment tests strain on a physical object like a pitcher, flask or drinking bottle, the design space models the shape of the physical object, and the design points distributed over the design space represents test points for strain. The dimensions of the design space define continuous variables for the design space (e.g., the height, width, and length of the object). The bottle in the experimental test, for example, may be a narrow-necked container made of impermeable material of various sizes to hold liquids of various temperatures.
In some experiments, it also helpful to observe how design options for the design space would influence the experiments. A categorical factor can be used to describe a design option or level at a design point for the design space. A categorical factor for the design space of the bottle could be a material type, with each of the design points taking on one of a set of levels that represent material types in the experiment. The material types for the bottle, for example, may be glass, metal, ceramic, and/or various types of plastic. In those cases where categorical factors are also employed, particularly on a non-rectangular design space like a bottle, it can be difficult to distribute the levels uniformly across the design.